data blending, caching and optimizing

Data Blending, Caching and Optimizing

Alma Martin

#Logi16

ALMA MARTINProduct ManagerLogi [email protected]

Here is an interesting fact about myself few people know.

ABOUT ME

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#Logi16

► The Data Problem

► How Logi addresses the Data Problem

► Logi DataHub Overview

WHAT WE ARE GOING TO LEARN TODAY

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The DATA Problem

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Data is often the biggest challenge of self-service analytics

Preparing Data for Analytics is Hard

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The Data Problem in Self Service Analytics

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Data lives in different places.

Organizations outsource applications to run their business (e.g. CRM, Sales, Marketing)

Accessing Data

RDBMS Applications Files

Half of the organizations are accessing external data sources*

*MQ Survey for BI and Analytic Platforms

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Accessing Data


Transactional systems are often not ready for analysis.

Need to blend data across sources to get a 360° view of the business.

Acquiring Data


#Logi16


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Accessing Data


Transactional systems are often not ready for analysis.

Need to blend data across sources to get a 360° view of the business.

Acquiring Data


Data needs to be refreshed and up to date for reporting.

Accessing and reporting on data in a performant experience.

Managing Data


OUR SOLUTIONLogi DataHub

Connect and acquire data, including files, databases, and cloud applications

Create, prepare, and manage dataviews for self-service analysis

Speed data prep with smart profiling, joining, and data enrichment

Accelerate performance for large data sets with a self-tuning, easy to maintain columnar data store

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Connect

• Applications

• Databases

• Files

Data Connectors

Author

• Joining objects

• Blending data sources

• Filter objects

Dataview Authoring

Cache

• Columnar store

• Self-tuning

• Scheduled refresh

Data Repository

Prepare

• DataSmart profiling

• Calculated columns

• Multi-part text

Data Enrichment

… For Self-Service

• Element in Logi Studio

• Info, SSM, Discovery

• Columnar store for Vision

Logi Integration

Create and Manage Dataviews

@soulety

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Primary DataHub Use Cases

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Offload transactional systems that are not optimized for analysisEnsure transactional system is not overloaded with analytical requests

Blend data from multiple sourcesCombine data from databases, applications and files into a single dataview

Support application data sources not included with Logi InfoExtends self-service analysis (SSM) to application sources

Create and manage dataviews for self-service analyticsSelf-managed data repository that does not require DBAs to administer

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Offload transactional systems from analytical requests

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Info Analytic Application

Transactional Application

Data is optimized for transactions

(inserts / updates)

Data is optimized for reporting and analysis

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Offload transactional systems from analytical requests

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Franchise Management Software

Transactional system overloading concerns with self service reporting.

Healthcare Solutions

Managed and self service solutions that require isolation of the

transactional system.

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Blend data from DBs, Cloud Applications, and Files

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Sales & Marketing Files

OFX

DatabasesFinance / ERP

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• Salesforce Connect

In App Data Blending Solutions Are Limited

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Connects Salesforce data to external sources ✓Recommended for big (external) datasets Follows security rules defined by the company Generates reports and charts from blended data External data can be used in formulas

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Extended Support for Application Sources in Info

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Info Supported SourcesDataHub Supported Sources

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Self-managed data repository that does not require DBAs to administer

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• No need to tune/index DB for self-service demands

• Minimal involvement from DBAs

• Faster deployment

Using Logi DataHub

#Logi16

Data Authoring in 5 Steps

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1.Create a Source

2.Build your Dataview

3. Enrich your Dataview

4.Define a Data Refresh Schedule

5.Connect to Logi Info

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1. Create a Source

Establish data connectivity

Applications Databases Files

OFX

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2. Build a Dataview

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Define and cache an optimized table that blends data across sources

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3. Enrich your Dataview

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Create calculated columns, adjust column names and types, etc.

New Col 1

New Col 2

New Col 3

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104105106

ID100101

103102

4. Schedule Data Cache Refresh

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Full Replace or Incremental Append

Source Data DataviewID

100101102103

104105106

ID100101

103102

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4. Schedule Data Cache Refresh

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Full Replace or Incremental Append

DataviewID

100101102103

104105106

ID100101

103102

Source Data

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5. Connect to Logi Info

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Use Dataviews for Self Service reporting and custom Logi Apps

Interactive Dashboards & Reports Data Analysis SharingData Query AuthoringDiscovery

BRINGING IT ALL TOGETHER

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Logi Analytics for Self-Service

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Learn more with the Gartner 2016 Critical Capabilities Report for BI and Analytics Platforms

https://goo.gl/IGNRO5




data blending, caching and optimizing

Data & Analytics